LEADER 02953nam  22006135  450 
001 9910300250203321
005 20250408085140.0
010   $a3-662-48344-0
024 7 $a10.1007/978-3-662-48344-2
035   $a(CKB)3710000000476913
035   $a(EBL)4178938
035   $a(SSID)ssj0001585490
035   $a(PQKBManifestationID)16264597
035   $a(PQKBTitleCode)TC0001585490
035   $a(PQKBWorkID)14864339
035   $a(PQKB)11579975
035   $a(DE-He213)978-3-662-48344-2
035   $a(MiAaPQ)EBC4178938
035   $a(PPN)190522763
035   $a(EXLCZ)993710000000476913
100   $a20150915d2015      u|         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aRankings and Preferences $eNew Results in Weighted Correlation and Weighted Principal Component Analysis with Applications /$fby Joaquim Pinto da Costa
205   $a1st ed. 2015.
210  1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2015.
215   $a1 online resource (95 p.)
225 1 $aSpringerBriefs in Statistics,$x2191-5458
300   $aDescription based upon print version of record.
311 08$a3-662-48343-2 
320   $aIncludes bibliographical references.
327   $aIntroduction -- The Weighted Rank Correlation Coefficient rW -- The Weighted Rank Correlation Coefficient rW2  -- A Weighted Principal Component Analysis, WPCA1: Application to Gene Expression Data -- A Weighted Principal Component Analysis (WPCA2) for Time Series Data -- Weighted Clustering of Time Series -- Appendix -- References.
330   $aThis book examines in detail the correlation, more precisely the weighted correlation, and applications involving rankings. A general application is the evaluation of methods to predict rankings. Others involve rankings representing human preferences to infer user preferences; the use of weighted correlation with microarray data and those in the domain of time series. In this book we present new weighted correlation coefficients and new methods of weighted principal component analysis. We also introduce new methods of dimension reduction and clustering for time series data, and describe some theoretical results on the weighted correlation coefficients in separate sections.
410  0$aSpringerBriefs in Statistics,$x2191-5458
606   $aStatistics
606   $aBiometry
606   $aStatistical Theory and Methods
606   $aBiostatistics
615  0$aStatistics.
615  0$aBiometry.
615 14$aStatistical Theory and Methods.
615 24$aBiostatistics.
676   $a519.537
700   $aPinto da Costa$b Joaquim$4aut$4http://id.loc.gov/vocabulary/relators/aut$0755704
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910300250203321
996   $aRankings and preferences$91522865
997   $aUNINA